A player with no modding knowledge told the AI what he wanted for his Big Ambitions game and set it to Opus high. Five minutes later he had a mod that worked in the game, shared on Steam Workshop as Learn on the Job.
Creator Matthew Berman describes giving an AI access to his local machine on a standing weekly job: it scans every file, finds deletion candidates totalling about 380GB, and sorts them into low, medium and high risk. The bot operates under one hard rule — it may categorize but must never delete anything itself.
A maker had an LLM design a circuit board by running KiCad headlessly from a terminal, checking the design in a loop until it passed every rule check. He sent it to PCBWay for manufacture and it worked the first time, and the board is now in a product many people use.
Creator took on a $30/week family-of-4 budget challenge with AI, asking it to start from what she already had in her pantry. The AI produced 7 dinner ideas, a grocery list, and a price comparison; her Walmart haul came to $29.66, under budget.
Used nit-picking history-teacher agents to evaluate a few hundred generated stories for accuracy, and pointed the AI at HN comments to aggregate issues and fix them with his OK; reported issues mostly fixed.
He asks the AI Agent to caption a video in Palmier Pro the same way as the previous one, and it does it from what it remembers. If there is no voice transcript, it writes code to make the captions happen.
Someone had the AI build a trade-alpha dashboard from his trade confirmation emails and benchmark the results against SPY. The agent turned scattered confirmations into a performance benchmark.
He saved articles and never read them, because on his phone he ended up on social media or email instead. So he built a reading app with AI and the AI that bundles his saved articles into one EPUB for his Xteink X4 Pro e-reader.